Key points are not available for this paper at this time.
Multiple sclerosis has undergone a therapeutic revolution over the past three decades. Randomized clinical trials and real-world data demonstrate that modern disease-modifying therapies substantially reduce relapse rates and acute inflammatory activity detected by magnetic resonance imaging (MRI). However, disability accumulation increasingly occurs independent of relapse activity, highlighting progression biology as the principal unmet need. Converging epidemiological and molecular evidence supports a pivotal role for Epstein-Barr virus (EBV) infection in disease initiation, whereas later stages appear dominated by brain-intrinsic mechanisms, including compartmentalized inflammation, microglial activation, failure of remyelination and accelerated biological ageing. Population-based cohorts demonstrate that early high-efficacy therapy improves long-term outcomes, yet the risk of progression rises markedly after midlife despite effective relapse suppression. Emerging biomarkers, such as serum neurofilament light chain, glial fibrillary acidic protein, paramagnetic rim lesions and advanced quantitative MRI metrics, now enable more granular monitoring of progressive pathology. Integration of imaging, fluid biomarkers, genetics and machine learning offers opportunities for individualized benefit-risk stratification. Brain-penetrant Bruton's tyrosine kinase inhibitors, CD40 ligand-targeting biologics, refined B-cell-depleting strategies and emerging chimeric antigen receptor T-cell therapies represent promising approaches to target different aspects of compartmentalized inflammation and smoldering disease biology. Future management will require mechanism-informed treatment algorithms that align therapeutic choice with dominant disease drivers while incorporating comorbidity management, de-escalation strategies and potential EBV-targeted preventive approaches to optimize outcomes across the entire disease course.
Piehl et al. (Tue,) studied this question.